Some thoughts on the data revolution in Uganda

Development Initiatives (DI) and Development Research and Training (DRT) are working on a ‘Joined-Up Data Uganda’ pilot programme in two rural districts. We are attempting to join up disaggregated data sets from various sources to create usable sub-district (sub-county and parish level) information. Our target users are district officials and community-based organisations.

The time has come for all those committed to this idea to move beyond the theory and focus on what the Data Revolution will mean in practice. Both DI and DRT are committed to playing a practical role in the Data Revolution: delivering the right information in the right format to the right people at the right time.

These notes are based on my limited experience working in Uganda and on the observations of our colleagues in DRT who understand the challenges and opportunities of accessing and using information in Uganda better than most. Please take note of the disclaimers at the bottom of these notes; these hopefully provide context to these thoughts.

Uganda produces a lot of good data…

The Uganda Bureau of Statistics (UBOS) is regarded as one of the best national statistics offices in Africa. It curates data collected by itself and a range of administrative systems. It publishes a range of nationally aggregated statistics on a relatively timely basis.

UBOS is rolling out a Community Information System, which is aimed at empowering communities to collect, manage and use data for planning and monitoring purposes. It is starting to publish (albeit in pdf format) sub-district data from household surveys in 47 of Uganda’s 112 districts (unfortunately the districts we are working in are not part of their pilot).

The Ministry of Finance, particularly through its Budget website, produces excellent, disaggregated data; not only financial data, but also district-level work plans and performance reports.

The Health Management Information System (HMIS) and Education Management Information System (EMIS) both collect and store a wide range of good, timely data from clinics and schools upwards.

From anecdotal evidence it appears that data collection carried out by UBOS for the 2014 Census went very well (with the exception of high-density areas of Kampala).

This wealth of data is atypical of most African countries. Uganda’s priorities are thus different from other countries. A one-size-fits-all data revolution won’t work.

… but most of it is not accessible

With the exception of District Budgets and the pilot Community Information System, no disaggregated data is readily available.

The vast majority of data that is accessible is only available in pdf format.

UNEB sells its data at exorbitant rates (to obtain the complete dataset of 2014 PLE results would cost UGX22 million; that is US$7,000).

UBOS and other line ministries and agencies generally appear to be committed to the private sharing of data with any institution that formally seeks official approval from the chief executive.

It is relatively easy, through personal contacts, to obtain data informally through junior officials in the various agencies. While these officials ask that the use of data cannot be traced back to them, the fear level is best described as relaxed. Our experience is that these officials do not risk their positions for personal gain, but because they think that the data they work with should be used more widely.

Reasons given for not making data accessible include that the integrity of the data is at stake if users can edit and republish it, and that those that need the data already get it through formal relationships and established channels.

It would be fair to conclude that, in general, Ugandan institutions are committed to the use of their data in both aggregated and disaggregated format, but that their definition of the legitimate user group is a limited one.

Senior officials, in general, appear not to be persuaded by current thinking on open government and open data. The concept of ‘open data’ in Uganda currently belongs to civil society.

Experience from the districts

In the districts in which we have been working, officials are hungry for meaningful information that will help them improve their performance. They have been keen to engage. They have been open in sharing what data they have. The offer of a district education officer to drive 60km to find an internet connection to send us some data is indicative of the spirit of cooperation that exists.

Our first attempts at joining up data – budgets, populations and results – show that the key to success is deciding what data to select in order to tell meaningful stories. Our first pilots have illustrated that the information we have produced from the selected data do not tell a meaningful story. This is a story in itself.

We need to listen to the intuitive reasoning and explanations of those working with their problems at first-hand, and then find the right data to confirm or disprove their theories. This is an important lesson we have learned.

Civil registration

“No one should be invisible” is how the executive summary of A World That Counts ends. If we don’t know where people are we cannot plan.

UNICEF has supported the establishment of a Mobile Vital Record Systems (MRVS), which is yielding promising results although it is hampered by insufficient funding and a system design flaw that defines the geographic location of the birth to be the point of registration, not the child’s home.

It is reasonable to assume that in 10 years time the URSB will be producing credible data on births.

While it is a legal requirement for Ugandan citizens to register deaths there is, in fact, no credible data collected on deaths, let alone causes of death. Nor is there any reason to believe under current priorities that a solution is being seriously considered. The URSB lacks finances. UNICEF has supported registration of births but “is not interested” in deaths. The MRVS has a module for death registration but it is not commissioned.

Causes of death

Some of the most important data that a health ministry needs to effectively allocate its resources is where and why people die. Accurate data on mortality does not exist in Uganda.

The otherwise excellent HMIS is the main source of data on most causes of death. But it is a facility-based reporting system: many people die at home and even when they do die in a clinic or hospital, reporting the true cause of death (such as maternal mortality) may reflect badly on the facility’s performance.

Maternal mortality data comes from the Demographic and Health Survey conducted every five years by UBOS. The most recent, in 2011, surveyed 10,086 households, interviewing 9,247 women and 2,573 men. There is substantive criticism of this survey being totally unrepresentative.

Counting or calculating: Administrative data or surveys?

The majority of Ugandan Millennium Development Goal (MDG) Indicators are calculated from Household or Demographic and Health surveys. The proposed draft indicator methodologies for the Sustainable Development Goals (SDGs) continue this practice.

Both methodologies record the fact that for many indicators administrative data is the preferred option, but the lack of any data (or reliable data) means that surveys are the fallback position.

While this was perfectly understandable for the MDGs, the SDGs are being developed within the explicit context of the Data Revolution. The SDGs therefore need to do two things:

Firstly all SDG policies should stress the importance for all countries to prioritise the financing and development of sustainable administrative data systems.

Secondly, as and when credible administrative data relevant to an SDG indicator becomes available, this data should replace survey data and the indicator should, if necessary, be rebased in light of the more accurate administrative data.

Technology and big data

Some of the biggest challenges facing a national (not just Kampala-based) Data Revolution in Uganda are electricity supply, internet access and computer equipment.

Uganda is home to a number of potentially ground-breaking uses of SMS technology, thanks mainly to UNICEF’s Innovation Labs. Usable data from a number of these systems should start becoming available over the next few years.

The only big datasets that exist in Uganda are those owned by the mobile phone companies. The UN Global Pulse initiative opened its first African lab in Kampala and is conducting research on population movements. It has also invested in a questionable study that uses purchases of mobile airtime credit to assess food security.

From the above it is reasonable and realistic to assume that big data and high technology solutions are (correctly) way down the list of Uganda’s priorities.

Recommendations

Any new funding from external sources needs to be channelled through the budget to ensure that donors are kept at arm’s length from the prioritisation of improvements to these systems.

The budget work of the Ministry of Finance Planning and Economic Development and UBOS’ Community Information System should be championed as examples of best practice.

The Government of Uganda needs persuading that it is in its own interest to make the wealth of good data that it collects more accessible and usable.

All actors in the Data Revolution should prioritise the production of good information from available data to build the use case for the government

Disclaimer

This is not a comprehensive nor an academic study. It is based on the work we have been doing on our Joined-Up Data Uganda (JUDU) programme, seeking, accessing and appraising data and engaging with a few agencies.

Our work has to date focussed on demographic, budget, health and education data. Our work focuses on sub-district data in two districts. We have no experience in assessing national datasets of district-level data. I have no knowledge of the state of macro-economic statistics or economic administrative data (agriculture, employment, industry, etc).

I am not a statistician. PARIS21‘s excellent new Metabase is the authoritative source assessing statistical capacity. I am an information architect concerned with the availability of data and its rendering into usable information for national and sub-national decision making.

I make a number of sweeping observations that, given my limited experience, may be considered presumptuous. I do so deliberately because I think it is the best way to take the debate on the Data Revolution forward.